16 Oct
2019

OEE and Predictive Maintenance

Learn how monitoring OEE in real time can enable predictive machinery maintenance capabilities.

OEE
OEE et maintenance prédictive

In today’s competitive manufacturing environment, Industry leaders search for even the smallest improvements to enhance overall production. One method which has been shown to sometimes significantly increase production across multiple manufacturing markets is the Overall Equipment Effectiveness method. Overall Equipment Effectiveness (OEE) is a key performance indicator which measures equipment’s level of productivity.

By understanding a piece of equipment’s level of productivity, the owner can reduce the number of defective products, optimize production processes, and even predict equipment maintenance needs.

The first step in grasping the OEE method is understanding the necessary calculations. 

Calculate OEE

OEE is calculated utilizing three metrics: 

  1. Availability: How often does the equipment function when required?
  2. Performance: How much does the equipment produce?
  3. Quality: How many defects does the equipment produce?

Each metric can be calculated using the equations listed below:

Availability is calculated by dividing the amount of time the equipment functions by the amount of time the equipment should function. A perfect piece of equipment will have a run time of 8-hours in an 8-hour production shift. Issues such as breakdowns and maintenance repairs will decrease the run time of the equipment as well as the availability. 

Availability = Run Time / Production Time

Performance is calculated by multiplying the fastest possible time to manufacture one piece and the total number of pieces produced (including defective ones). This value is then divided by the amount of time the machine is spent running. The slower a machine produces items, the lower the performance. 

Performance = (Ideal Cycle Time X Total Count) / Run Time

Quality is calculated by dividing the amount of non-defective pieces produced by the total amount of pieces produced. 

Quality = Passing Count / Total Count

And finally, OEE is calculated by multiplying all three factors: availability, performance, and quality. 

OEE = Availability X Performance X Quality

What does OEE tell you?

In an ideal world, equipment would receive 100% for all values. Unfortunately, this is not the case. Luckily, benchmarks have been developed so that owners may gauge the state of their equipment compared to industry standards.

Listed below is a breakdown of several benchmarks for the OEE method:

 

Ideal

Standard

Availability

90%

80%

Performance

95%

80%

Quality

99%

95%

OEE

85%

60%

 

Based off the benchmark table, you should be able to ascertain the performance level of your equipment. 

By implementing Smart Factory technology, you can access machinery data in real time. This lets you build an OEE model for each key piece of machinery. A slide in OEE for a machine tells you that at least one factor, availability, performance and quality is deteriorating. This can be a signal that a machine is in need of maintenance before a significant breakdown occurs.

Overall, this method of predicting maintenance has the potential to save companies not only production time, but also a considerable amount of capital by maintaining high performance levels with minimum equipment unplanned outages.

Interested in gathering real time factory analytics data to empower your predictive maintenance program?

Want to learn more?
Download the ebook
Related blog articles

Articles connexes

Retour au blog
Nous vous remercions ! Votre demande a bien été reçue !
Oups ! Un problème s'est produit lors de l'envoi du formulaire.
13
Juillet 2023

5 Ways Production Monitoring Helps Reduce Turnover and Bridge the Skills Gap

English
19
Avril 2021

Learn How to Improve Raw Materials Yield by Connecting Your Scales and Checkweighers

English
22
Oct. 2021

How Digital Tools Can Help You Measure OEE In the Manufacturing Industry

English

Articles connexes

Retour au blog
Nous vous remercions ! Votre demande a bien été reçue !
Oups ! Un problème s'est produit lors de l'envoi du formulaire.
10
mai 2019

Pénurie de main d'oeuvre dans le secteur manufacturier québécois

Un article paru dans lapresse+ présente le paradoxe d'un marché manufacturier québécois qui connait une belle expansion mais dont l'essor pourrait être freiné par le manque de main d'oeuvre qui dépasse les 20% dans certaines PME québécoises.

French
28
Fév 2020

SaaS Training and User Adoption Best Practices

Implementing a SaaS solution takes having a strong user adoption plan.

English
27
Août 2018

La CCMM publie un cahier spécial sur la main d'oeuvre 4.0 dans LaPresse+

La CCMM publie un cahier spécial Industrie 4.0 dans LaPresse+ du 20 aout 2018. Le cahier propose des pistes de solutions pour faire face aux enjeux de recrutementent de formation de la main d'oeuvre 4.0

French